Effective human–AI work design for collaborative decision-making
ISSN: 0368-492X
Article publication date: 5 July 2022
Issue publication date: 9 November 2023
Abstract
Purpose
With the increase in the adoption of artificial intelligence (AI)-based decision-making, organizations are facilitating human–AI collaboration. This collaboration can occur in a variety of configurations with the division of labor, with differences in the nature of interdependence being parallel or sequential, along with or without the presence of specialization. This study intends to explore the extent to which humans express comfort with different models human–AI collaboration.
Design/methodology/approach
Situational response surveys were adopted to identify configurations where humans experience the greatest trust, role clarity and preferred feedback style. Regression analysis was used to analyze the results.
Findings
Some configurations contribute to greater trust and role clarity with AI as a colleague. There is no configuration in which AI as a colleague produces lower trust than humans. At the same time, the human distrust in AI may be less about human vs AI and more about the division of labor in which human–AI work.
Practical implications
The study explores the extent to which humans express comfort with different models of an algorithm as partners. It focuses on work design and the division of labor between humans and AI. The finding of the study emphasizes the role of work design in human–AI collaboration. There is human–AI work design that should be avoided as they reduce trust. Organizations need to be cautious in considering the impact of design on building trust and gaining acceptance with technology.
Originality/value
The paper's originality lies in focusing on the design of collaboration rather than on performance of the team.
Keywords
Acknowledgements
Ethical approval: This research does not contain any studies performed with animals by any of the authors. The procedures followed in the study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Informed consent: Informed consent was obtained from all the individual participants included in the study.
Conflict of interest: The authors declare that they have no conflicts of interest. There are no relevant financial or nonfinancial interests to disclose.
Citation
Jain, R., Garg, N. and Khera, S.N. (2023), "Effective human–AI work design for collaborative decision-making", Kybernetes, Vol. 52 No. 11, pp. 5017-5040. https://doi.org/10.1108/K-04-2022-0548
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited